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	<pub:Article rdf:about="http://ebiquity.umbc.edu/paper/html/id/1033/Computational-Understanding-of-Narratives-A-Survey">
		<rdfs:label><![CDATA[Computational Understanding of Narratives: A Survey]]></rdfs:label>
		<pub:title><![CDATA[Computational Understanding of Narratives: A Survey]]></pub:title>
		<pub:publishedOn rdf:datatype="&xsd;dateTime">2022-09-05T00:00:00-05:00</pub:publishedOn>
		<pub:abstract><![CDATA[Storytelling and the delivery of societal narratives enable human beings to communicate, connect, and understand one another and the world around them. Narratives can be defined as spoken, visual, or written accounts of interconnected events and actors, generally evolving through some notion of time. Today, information is typically conveyed over online communication mediums, such as social media and blogging websites. Consequently, the act of narrative delivery itself has shifted from simply imparting information through self-contained structures, such as books, to more fragmented structures, such as social media websites, where evolving story events are constructed over multiple online sources. Ubiquitous online conversation can manifest into sophisticated narratives that have the potential to influence widespread user interpretations of cultural sentiments, attitudes, values, as well as geopolitical events and facts. As a result, narratives are actively being used as strategic tools for shaping local events, promoting collective opinions, and asserting ideologies and propaganda, making them sources of interest for identifying themes, intentions, and goals across multiple communities and potential adversaries. Identifying fragmented narratives, extracting thematic and temporal components that constitute evolving narratives, and locating signs of active rhetoric framing tactics are difficult to detect and analyze without large-scale automation. This problem can be addressed through the use of natural language understanding technologies. Our goal is to document and discuss methods to efficiently construct, extract, and detect evolving online narratives. The novel contribution of this paper is the formal collation and documentation of such technologies and research areas, as well as extensive discussion on open research challenges and goals in the definition, identification, construction, generation, and representation of online narratives. To our knowledge, there is currently no existing formal documentation that organizes and provides extended discussion on narrative understanding research areas and open challenges.]]></pub:abstract>
		<pub:pages><![CDATA[101575-101594]]></pub:pages>
		<pub:note><![CDATA[Author's version
<br/>
DOI: <a href="https://doi.org/10.1109/ACCESS.2022.3205314">10.1109/ACCESS.2022.3205314</a>
<br/>
<img src="https://i.imgur.com/1KunAXc.png" style='height: 90%; width: 90%; object-fit: contain; display: block; margin-left: auto; margin-right: auto;'>]]></pub:note>
		<pub:volume><![CDATA[10]]></pub:volume>
		<pub:organization><![CDATA[IEEE]]></pub:organization>
		<pub:counter>3312</pub:counter>
		<pub:tag><![CDATA[ai]]></pub:tag>
		<pub:tag><![CDATA[language understanding. nlp]]></pub:tag>
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		<pub:booktitle><![CDATA[IEEE Access]]></pub:booktitle>
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							<person:Person rdf:about="http://ebiquity.umbc.edu/person/html/Tim/Finin"><person:name><![CDATA[Tim Finin]]></person:name><rdfs:label><![CDATA[Tim Finin]]></rdfs:label></person:Person>
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									<person:Person rdf:about="http://ebiquity.umbc.edu/person/html/Priyanka/Ranade"><person:name><![CDATA[Priyanka Ranade]]></person:name><rdfs:label><![CDATA[Priyanka Ranade]]></rdfs:label></person:Person>
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